Furniture placement is challenging because it requires jointly optimizing a variety of functional and visual criteria. Skilled interior designers follow numerous high-level guidelines in producing furniture layouts. In a living room, for example, the furniture should support comfortable conversation, align with prominent features of the space, and collectively form a visually balanced composition. In practice, these guidelines are often imprecise and sometimes contradictory. Experienced designers learn to balance the tradeoffs between the guidelines through an iterative trial-and-error process.
Yet, most people responsible for furnishing a home have no training in interior design. They may not be aware of interior design guidelines, and they are unlikely to have the tacit knowledge and experience required to optimally balance the tradeoffs. Instead, such amateur designers rely on intuitive rules such as pushing large furniture items against the walls. These intuitive rules often lead to functionally ineffective and visually imbalanced arrangements. The resulting furniture layouts may not “look or feel right,” and even worse, the amateur designer “cannot pinpoint what the problems are.”
Assisted direct manipulation interfaces have been studied in computer graphics, dating back to, for example, Ivan Sutherland's Sketch-Pad. In the context of architectural design, conventional approaches have described interfaces for creating floorplans, for example. Such an interface can support local constraints and invoke discrete local search whenever the user drives the layout into a challenging configuration. Other approaches use sequential quadratic programming to optimize an arrangement of rectangles in response to interactive manipulation. These approaches assist the layout of general rectangular arrangements but do not incorporate furniture layout guidelines.
Focusing on furniture layout, a conventional approach uses “object association” constraints that are designed to facilitate direct manipulation of furniture arrangements. For example, the user can constrain a bookshelf to slide along walls without penetration or separation. Certain other approaches present a constraint-based furniture layout system that incorporates pairwise relationships which enforce stability, non-penetration, and alignment. Others describe an agent-based procedure for furniture layout.
Layout problems arise in a number of domains. For example, one strategy is to use optimization techniques to find a layout that satisfies domain-specific criteria. Researchers have applied this optimization approach to circuit board layout, graph layout, component layout in product design, document layout, UI layout, label layout, and architectural floor plan layout, for example. Most of these approaches were developed for off-line layout and do not support direct manipulation or generation of multiple high-quality alternatives.
While tools may be available for visualizing furniture arrangements, such tools do not alleviate the physical strain of moving furniture pieces to prototype different layouts. The placement of the furniture relies entirely on the user's expertise, which is often insufficient to produce effective furniture arrangements.
Therefore, there is a need for a method and system that assists furniture placement by providing preferred suggestions based on interior design and other guidelines.